Archive for the ‘Behavioral Economics’ Category

Eugene Fama, Lars Peter Hansen, and Robert Shiller won the Nobel Prize in Economics this morning for their work studying asset prices. In one sense, they are a motley trio: Fama is famous for emphasizing efficient markets, Shiller for emphasizing investor psychology and inefficient markets, and Hansen for high-tech econometric techniques that are used well beyond finance. The unifying theme is their shared interest in understanding the predictability, if any, of asset prices.

The Royal Swedish Academy of Sciences posted an accessible summary of their work. Here’s the intro:

There is no way to predict whether the price of stocks and bonds will go up or down over the next few days or weeks. But it is quite possible to foresee the broad course of the prices of these assets over longer time periods, such as, the next three to five years. These findings, which may seem both surprising and contradictory, were made and analyzed by this year’s Laureates, Eugene Fama, Lars Peter Hansen and Robert Shiller.

Fama, Hansen, and Shiller have developed new methods for studying asset prices and used them in their investigations of detailed data on the prices of stocks, bonds and other assets. Their methods have become standard tools in academic research, and their insights provide guidance for the development of theory as well as for professional investment practice. Although we do not yet fully understand how asset prices are determined, the research of the Laureates has revealed a number of important regularities that are helping us to arrive at better explanations.

…

The predictability of asset prices is closely related to how markets function, and that’s why researchers are so interested in this question. If markets work well, prices should have very little predictability. This statement may seem paradoxical, but consider the following: suppose investors could predict that a certain stock would increase a lot in value over the next year. Then they would buy the stock immediately, driving up the price until it is so high that the stock is no longer attractive to buy. What remains is an unpredictable price pattern, with random movements that reflect the arrival of news. In technical jargon, prices then follow a “random walk.”

There are, however, reasons why prices may follow somewhat predictable patterns even in a well-functioning market. A key factor is risk. Risky assets are less attractive to investors, so on average, a risky asset will need to deliver a higher return. A higher return for the risky asset means that its price can be predicted to rise faster than for safe assets. To detect market malfunctioning, then, one would need to have an idea of what a reasonable compensation for risk ought to be. The issue of predictability and the issue of normal returns that compensate for risk are intertwined. The three Laureates have shown how to disentangle these issues and analyze them empirically.

Creating property rights has helped protect fisheries while making the fishing industry more efficient, according to a nice blog post by Eric Pooley of the Environmental Defense Fund (ht: Dick Thaler). Writing at the Harvard Business Review, Pooley notes the success of the “catch share” approach to fisheries management:

The Gulf of Mexico red snapper fishery, for example, was on the brink of collapse in the early part of the last decade. Fishermen were limited to 52-day seasons that were getting shorter every year. The shortened seasons, an attempt to counter overfishing, hurt fishermen economically and created unsafe “derbies” that often forced them to race into storms like the boats in The Deadliest Catch.

This short window also meant that all of the red snapper were being caught and brought to market at the same time, creating a glut that crashed prices. Many fishermen couldn’t even cover the cost of their trip to sea after selling their fish.

A decade ago, the Environmental Defense Fund began working with a group of commercial red snapper fishermen on a new and better way of doing business. Together, we set out to propose a catch share management system for snapper.

Simply put, fishermen would be allocated shares based on their catch history (the average amount of fish in pounds they landed each year) of the scientifically determined amount of fish allowed for catch each year (the catch limit). Fishermen could then fish within their shares, or quota, all year long, giving them the flexibility they needed to run their businesses.

This meant no more fishing in dangerously bad weather and no more market gluts. For the consumer, it meant fresh red snapper all year long.

After five years of catch share management, the Gulf of Mexico red snapper fishery is growing because fishermen are staying within the scientific limits. Boats that once suffered from ever-shortening seasons have seen a 60% increase in the amount of fish they are allowed to catch. Having a percentage share of the fishery means fishermen have a built-in incentive to husband the resource, so it will continue to grow.

Please read the rest of his piece for additional examples in the United States and around the world. Catch shares don’t deserve all the credit for fishery rebounds (catch limits presumably played a significant role), but they appear to be a much better way to manage limited stocks.

One small quibble: Pooley refers to catch shares as an example of behavioral economics in action. That must be a sign of just how fashionable behavioral economics–the integration of psychology into economics–has become. In this case, though, the story is straight-up economics: incentives and property rights.

Does your brain freeze when offered too many options? Do you put off repainting your bathroom because you can’t bear to select among fifty shades of white (or, for the more adventurous, grey)?

If so, take heart. A famous experiment by psychologists Mark Lepper and Sheena Iyengar, published in 2000, suggests that you are not alone. In supermarket tests, they documented what’s known as the Paradox of Choice. Customers offered an array of six new jam varieties were much more likely to buy one than those offered a choice of 24.

That makes no sense in the narrow sense of rationality often used in simple economic models. More choice should always lead to more sales, since the odds are greater that a shopper will find something they want. But it didn’t. On those days, in those supermarkets, with those jams, more choice meant less buying.

This result resonates with many people. I certainly behave that way occasionally. With limited time and cognitive energy, I sometimes avoid or defer choices that I don’t absolutely need to make … like buying a new jam. Making decisions is hard. Just as consumers have financial budget constraints, so too do we have decision-making budget constraints.

Today’s TED Blog provides links and, naturally, videos for a series of studies documenting similar challenges of choice, from retirement planning to health care to spaghetti sauce. All well worth a view.

But how general are these results? Perhaps not as much as we’d think from the TED talks. A few years ago, Tim Harford, the Financial Times’ Undercover Economist, noted that some subsequent studies in the jam tradition failed to find this effect:

It is hard to find much evidence that retailers are ferociously simplifying their offerings in an effort to boost sales. Starbucks boasts about its “87,000 drink combinations”; supermarkets are packed with options. This suggests that “choice demotivates” is not a universal human truth, but an effect that emerges under special circumstances.

Benjamin Scheibehenne, a psychologist at the University of Basel, was thinking along these lines when he decided (with Peter Todd and, later, Rainer Greifeneder) to design a range of experiments to figure out when choice demotivates, and when it does not.

But a curious thing happened almost immediately. They began by trying to replicate some classic experiments – such as the jam study, and a similar one with luxury chocolates. They couldn’t find any sign of the “choice is bad” effect. Neither the original Lepper-Iyengar experiments nor the new study appears to be at fault: the results are just different and we don’t know why.

After designing 10 different experiments in which participants were asked to make a choice, and finding very little evidence that variety caused any problems, Scheibehenne and his colleagues tried to assemble all the studies, published and unpublished, of the effect.

The average of all these studies suggests that offering lots of extra choices seems to make no important difference either way. There seem to be circumstances where choice is counterproductive but, despite looking hard for them, we don’t yet know much about what they are. Overall, says Scheibehenne: “If you did one of these studies tomorrow, the most probable result would be no effect.”

In short, the Paradox of Choice is experiencing the infamous Decline Effect. As Jonah Lehrer noted in the New Yorker in late 2010, sometimes what seems to be scientific truth “wears off” over time. And not just in “soft” sciences like the intersection of psychology and economics, but in biology and medicine as well.

Some of that decline reflects selection pressures in research and publishing … and invitations to give TED talks. It’s easy to get a paper published if it documents a new a paradox or anomaly. Only after that claim has gained some mindshare does the marketplace then open to research showing null results of no paradox.

In Sunday’s New York Times, Richard Thaler laments that “as a general rule, the United States government is run by lawyers who occasionally take advice from economists.”

That makes for better policy than a tyranny of lawyers alone. But it certainly isn’t enough. Policy is ultimately about changing the way people behave. And to do that, you need to understand more than just economics (as an increasing number of economists, Thaler foremost among them, already recognize).

Thaler thus makes two important suggestions: First, he argues that behavioral scientists deserve a greater formal role in the policy process, perhaps even a Council of Behavioral Science Advisers that would advise the White House in parallel with the Council of Economic Advisers. Second, he urges government to engage in more experimentation so it can learn just what policy choices best drive behavior, and how.

As an example, he cites the efforts of Britain’s Behavioral Insights Team, which was created when David Cameron’s coalition government came to office in 2010.

As its name implies, the team (which he advises) works with government agencies to explore how behavioral insights can make policy more effective. Tax compliance is one example.

Each year, Britain sends letters to certain taxpayers—primarily small businesses and individuals with non-wage income—directing them to make appropriate tax payments within six weeks. If they fail to do so, the government follows up with more costly measures. Enter the Behavioral Insights Team:

The winning recipe comes from Robert B. Cialdini, an emeritus professor of psychology and marketing at Arizona State University, and author of the book “Influence: The Psychology of Persuasion.”

People are more likely to comply with a social norm if they know that most other people comply, Mr. Cialdini has found. (Seeing other dog owners carrying plastic bags encourages others to do so as well.) This insight suggests that adding a statement to the letter that a vast majority of taxpayers pay their taxes on time could encourage others to comply. Studies showed that it would be even better to cite local data, too

Letters using various messages were sent to 140,000 taxpayers in a randomized trial. As the theory predicted, referring to the social norm of a particular area (perhaps, “9 out of 10 people in Exeter pay their taxes on time”) gave the best results: a 15-percentage-point increase in the number of people who paid before the six-week deadline, compared with results from the old-style letter, which was used as a control condition.

Rewriting the letter thus materially improved tax compliance. That’s an important insight, and I hope it scales if and when Britain’s tax authority applies it more broadly.

But there’s a second lesson as well: the benefit of running policy experiments. Policymakers have no lack for theories about how people will respond to various policy changes. What they often do lack, however, is evidence about which theory is correct or how big the potential effects are. Governments on both sides of the Atlantic should look for opportunities to run such controlled experiments so that, to paraphrase Thaler, evidence-based policies can be based on actual evidence.

The fun economics story of the day is that Orbitz sometimes looks at your computer’s operating system to decide what hotel options to show you. Dana Mattioli breaks the story over at the Wall Street Journal:

Orbitz Worldwide Inc. has found that people who use Apple Inc.’s Mac computers spend as much as 30% more a night on hotels, so the online travel agency is starting to show them different, and sometimes costlier, travel options than Windows visitors see.

The Orbitz effort, which is in its early stages, demonstrates how tracking people’s online activities can use even seemingly innocuous information—in this case, the fact that customers are visiting Orbitz.com from a Mac—to start predicting their tastes and spending habits.

Orbitz executives confirmed that the company is experimenting with showing different hotel offers to Mac and PC visitors, but said the company isn’t showing the same room to different users at different prices. They also pointed out that users can opt to rank results by price.

My question: Would you feel any different if, instead, the WSJ emphasized that Windows users are directed to lower-priced hotels? For example, Windows users are prompted about the affordable lodgings at the Travelodge in El Paso, Texas. (Full disclosure: I think I once stayed there.)

As Mattioli notes, it’s important to keep in mind that Orbitz isn’t offering different prices, it’s just deciding which hotels to list prominently. And your operating system is just one of many factors that go into this calculation. Others include deals (hotels offering deals move up the rankings), referring site (which can reveal a lot about your preferences), return visits (Orbitz learns your tastes), and location (folks from Greenwich, CT probably see more expensive hotels than those from El Paso).

We are each constructed from a genetic blueprint, and then born into a world of circumstances that we cannot control in our most-formative years. The complex interactions of genes and environment mean that all citizens—equal before the law—possess different perspectives, dissimilar personalities, and varied capacities for decision-making. The unique patterns of neurobiology inside each of our heads cannot qualify as choices; these are the cards we’re dealt.

Because we did not choose the factors that affected the formation and structure of our brain, the concepts of free will and personal responsibility begin to sprout question marks. Is it meaningful to say that Alex made bad choices, even though his brain tumor was not his fault? Is it justifiable to say that the patients with frontotemporal dementia or Parkinson’s should be punished for their bad behavior?

It is problematic to imagine yourself in the shoes of someone breaking the law and conclude, “Well, I wouldn’t have done that”—because if you weren’t exposed to in utero cocaine, lead poisoning, and physical abuse, and he was, then you and he are not directly comparable. You cannot walk a mile in his shoes.

The legal system rests on the assumption that we are “practical reasoners,” a term of art that presumes, at bottom, the existence of free will. The idea is that we use conscious deliberation when deciding how to act—that is, in the absence of external duress, we make free decisions. This concept of the practical reasoner is intuitive but problematic.

The “practical reasoner” assumption is, of course, fundamental to much of economics as well. Used thoughtfully, it’s extremely useful for examining how reflective, ends-oriented agents behave. But it’s problematic, to say the least, if we assume that everyone is always a rational actor.

Eagleman argues that the criminal justice system should be sensitive to the cognitive differences among people. Some people murder as the result of calculated, rational decisions, but others murder because brain tumors destroy their ability to control themselves. Those differences matter when thinking about deterrence, treatment, and punishment.

On January 1, Washington DC introduced a 5-cent tax on disposable shopping bags at grocery, drug, convenience, and liquor stores. The fee had two goals: to reduce the number of bags, in particular plastic ones, that end up blighting the landscape and to raise funds for cleaning up the Anacostia River.

The fee appears to be succeeding on both counts, but not equally so. As Sara Murray and Sudeep Reddy report over at the Wall Street Journal, shoppers have cut back on bag use more than anticipated; as a result revenues are running below expectations:

[T]he city estimated that [bag use] would decline by 50% in the first year after the tax was imposed. …. [A]n informal survey of corporate headquarters for grocery stores and pharmacies with dozens of locations in the city estimated a reduction of 60% or more in the number of bags handed out. … Through the end of July, the city collected more than $1.1 million from the bag fee and small donations. At that rate, receipts are likely to fall short of the expected $3.6 million in the first year.

I’ve witnessed the sharp decline in bag use during my daily lunch run. Last year, the Subway folks would automatically put your sandwich and a napkin in a plastic bag. Now they ask if you want one. I always decline, as do most other customers.

Why has there been such a strong reaction to a nickel fee? I think it’s a combination of two factors.

The first is a traditional microeconomic explanation: there are often good substitutes for a disposable shopping bag. For example, I find it just as easy to carry the wrapped sandwich as to carry the old Subway bag. And if I buy some dental floss at CVS, I can just pop it in my pocket for the trip home. So even a relatively small fee can get results.

The second is a behavioral explanation: people act weird when things are free–they acquire things without really thinking about it. If you start charging a price–and thus change the default from “here’s your bag” to “do you want a bag?”–you can witness large responses.